Introducing Particle Swarm Optimization (PSO) to Invert Refraction Seismic Data

Poormirzaee, Rashed; Moghadam, Rasoul Hamidzadeh; Zarean, A.

doi:10.3997/2214-4609.20141978

Cited by 4 publications

(1 citation statement)

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“…PSO is quite recent in the framework of geophysical data inversion (Shaw and Srivastava, 2007;Yuan et al, 2009) and is not yet as widely as the other global optimization methods mentioned previously. However, it was successfully applied to surface-wave analysis (Song et al, 2012;Wilken and Rabbel, 2012), traveltime tomography (Tronicke et al, 2012;Luu et al, 2016), seismic refraction (Poormirzaee et al, 2014), seismic wave impedance inversion in igneous rock (Yang et al, 2017) and multifrequency GPR inversion (Salucci et al, 2017). Furthermore, Song et al (2012) have shown, in a comparative analysis, that PSO outperforms genetic algorithm and Monte-Carlo methods in terms of reliability and computational efforts.…”

Section: D Inversion Using Particle Swarm Optimizationmentioning

confidence: 99%

Assessment of Physical Properties of a Sea Dike Using Multichannel Analysis of Surface Waves and 3D Forward Modeling

Pageot¹,

Feuvre²,

Leparoux³

et al. 2017

Proceedings

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Seismic surface waves analysis methods have been widely developed and tested in the context of subsurface characterization and have demonstrated their effectiveness for sounding and monitoring purposes. Given their efficiency, surface waves methods have been used in a variety of contexts, including civil engineering applications. However, at this particular scale, many structures exhibit 3D geometries which drastically limit the efficiency of these methods since they are mostly developed under the assumption of a semi-infinite 1D layered medium without topography. Taking advantages of wave propagation modeling algorithm development and high-performance computing center accessibility, it is now possible to consider the use of a 3D elastic forward modeling algorithm for the inversion of surface wave dispersion. We use a parallelized 3D elastic modeling code based on the spectral element method which allows to obtain accurate synthetic data with very low numerical dispersion and a reasonable numerical cost. In this study, we choose a sea dike as a case example. We first show that their longitudinal geometry and structure may have a significant effect on dispersion diagrams of Rayleigh waves. Then, we investigate the sensitivity of the dispersion diagrams to small velocity and layer thickness perturbations, and show the limitations of the standard 1D surface wave methods approach. Finally, we demonstrate in this context the benefits of using both a 3D forward modeling engine and the whole dispersion diagram, instead of the dispersion curves only.

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